For senior or introductory graduate-level courses in digital signal processing. Developed by a group of six eminent scholars and teachers, this book offers a rich collection of exercises and projects which guide students in the use of MATLAB v5 to explore major topical areas in digital signal processing.

Quickly Engages in Applying Algorithmic Techniques to Solve Practical Signal Processing Problems With its active, hands-on learning approach, this text enables readers to master the underlying principles of digital signal processing and its many applications in industries such as digital television, mobile and broadband communications, and medical/scientific devices. Carefully developed MATLAB® examples throughout the text illustrate the mathematical concepts and use of digital signal processing algorithms. Readers will develop a deeper understanding of how to apply the algorithms by manipulating the codes in the examples to see their effect. Moreover, plenty of exercises help to put knowledge into practice solving real-world signal processing challenges. Following an introductory chapter, the text explores: Sampled signals and digital processing Random signals Representing signals and systems Temporal and spatial signal processing Frequency analysis of signals Discrete-time filters and recursive filters Each chapter begins with chapter objectives and an introduction. A summary at the end of each chapter ensures that one has mastered all the key concepts and techniques before progressing in the text. Lastly, appendices listing selected web resources, research papers, and related textbooks enable the investigation of individual topics in greater depth. Upon completion of this text, readers will understand how to apply key algorithmic techniques to address practical signal processing problems as well as develop their own signal processing algorithms. Moreover, the text provides a solid foundation for evaluating and applying new digital processing signal techniques as they are developed.

DIGITAL SIGNAL PROCESSING LABORATORY USING MATLAB is intended for a computer-based DSP laboratory course that supplements a lecture course on Digital Signal Processing. The book can be used either as a stand-alone text or in conjunction with Mitra's Digital Signal Processing: A Computer-Based Approach. The book includes 11 laboratory exercises, with each exercise containing a number of projects to be carried out on a computer. The book assumes that the reader has no background in MATLAB and teaches the reader, through tested programs in the first half of the book, the basics of this powerful language in solving important problems in signal processing. In the second half of the book, the student is asked to write the necessary MATLAB programs to carry out the projects.

This supplement to any standard DSP text is one of the first books to successfully integrate the use of MATLAB® in the study of DSP concepts. In this book, MATLAB® is used as a computing tool to explore traditional DSP topics, and solve problems to gain insight. This greatly expands the range and complexity of problems that students can effectively study in the course. Since DSP applications are primarily algorithms implemented on a DSP processor or software, a fair amount of programming is required. Using interactive software such as MATLAB® makes it possible to place more emphasis on learning new and difficult concepts than on programming algorithms. Interesting practical examples are discussed and useful problems are explored. This updated second edition includes new homework problems and revises the scripts in the book, available functions, and m-files to MATLAB® V7.

This textbook provides engineering students with instruction on processing signals encountered in speech, music, and wireless communications using software or hardware by employing basic mathematical methods. The book starts with an overview of signal processing, introducing readers to the field. It goes on to give instruction in converting continuous time signals into digital signals and discusses various methods to process the digital signals, such as filtering. The author uses MATLAB throughout as a user-friendly software tool to perform various digital signal processing algorithms and to simulate real-time systems. Readers learn how to convert analog signals into digital signals; how to process these signals using software or hardware; and how to write algorithms to perform useful operations on the acquired signals such as filtering, detecting digitally modulated signals, correcting channel distortions, etc. Students are also shown how to convert MATLAB codes into firmware codes. Further, students will be able to apply the basic digital signal processing techniques in their workplace. The book is based on the author's popular online course at University of California, San Diego.

Although Digital Signal Processing (DSP) has long been considered an electrical engineering topic, recent developments have also generated significant interest from the computer science community. DSP applications in the consumer market, such as bioinformatics, the MP3 audio format, and MPEG-based cable/satellite television have fueled a desire to understand this technology outside of hardware circles. Designed for upper division engineering and computer science students as well as practicing engineers and scientists, Digital Signal Processing Using MATLAB & Wavelets, Second Edition emphasizes the practical applications of signal processing. Over 100 MATLAB examples and wavelet techniques provide the latest applications of DSP, including image processing, games, filters, transforms, networking, parallel processing, and sound. This Second Edition also provides the mathematical processes and techniques needed to ensure an understanding of DSP theory. Designed to be incremental in difficulty, the book will benefit readers who are unfamiliar with complex mathematical topics or those limited in programming experience. Beginning with an introduction to MATLAB programming, it moves through filters, sinusoids, sampling, the Fourier transform, the z-transform and other key topics. Two chapters are dedicated to the discussion of wavelets and their applications. A CD-ROM (platform independent) accompanies the book and contains source code, projects for each chapter, and the figures from the book.

Signals and Systems Using MATLAB, Third Edition, features a pedagogically rich and accessible approach to what can commonly be a mathematically dry subject. Historical notes and common mistakes combined with applications in controls, communications and signal processing help students understand and appreciate the usefulness of the techniques described in the text. This new edition features more end-of-chapter problems, new content on two-dimensional signal processing, and discussions on the state-of-the-art in signal processing. - Introduces both continuous and discrete systems early, then studies each (separately) in-depth - Contains an extensive set of worked examples and homework assignments, with applications for controls, communications, and signal processing - Begins with a review on all the background math necessary to study the subject - Includes MATLAB® applications in every chapter

This text provides a broad introduction to the field of digital signal processing and contains sufficient material for a two-semester sequence in this multifaceted subject. It is also written with the practicing engineer or scientist in mind, having many observations and examples of practical significance drawn from the author's industrial experience. The first semester, at the junior, senior, or first-year graduate level, could cover chapters 2 through 7 with topics perhaps from chapters 8 and 9, depending upon the background of the students. The only requisite background is linear systems theory for continuous-time systems, including Fourier and Laplace trans forms. Many students will also have had some previous exposure to discrete-time systems, in which case chapters 2 through 4 may serve to review and expand that preparation. Note, in particular, that knowledge of probability theory and random processes is not required until chapters 10 and 11, except for section 7. 6 on the periodogram. A second, advanced course could utilize material from chapters 8 through 13. A comprehensive one-semester course for suitably prepared graduate students might cover chapters 4 through 9 and additional topics from chapters 10 through 13. Sections marked with a dagger Ct) cover advanced or specialized topics and may be skipped without loss of continuity. Notable features of the book include the following: 1. Numerous useful filter examples early in the text in chapters 4 and 5. 2. State-space representation and structures in chapters 4 and 11.